If you’re using chaining in pandas to pipeline a .csv, order can play a factor. Specifically, with filling in NaNs and reordering column names. It has to be done in that order. So, this works: diamonds = (pd.read_csv("../data/diamonds_raw.csv", index_col=[0]) .drop(['date', …

If you’re using chaining in pandas to pipeline a .csv, order can play a factor. Specifically, with filling in NaNs and reordering column names. It has to be done in that order. So, this works: diamonds = (pd.read_csv("../data/diamonds_raw.csv", index_col=[0]) .drop(['date', …